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mathematicians and computer scientists at the University of Southampton, the University of Oxford (lead node), Imperial College London, Queen Mary University of London, Durham University, and the University
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of classes, using Machine Learning (ML) techniques such as Decision Trees, K-Nearest Neighbors (KNN), XGBoost, Support Vector Machines (SVM), or Neural Networks. Explore and implement clustering algorithms
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dataset, GroupLens Research. grouplens.org [8] Statlog German Credit Data, UCI Machine Learning Repository. archive.ics.uci.edu [9] ERASER Benchmark, ERASER Project. eraserbenchmark.com [10] e-SNLI Dataset
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network engineering and angiogenesis 3). Applications of machine learning in cell and tissue engineering Candidates should have demonstrated publication records in cardiac and vascular engineering or
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with a focus on traditional machine learning (shallow learning) and deep learning methodologies. Knowledge of Data Science, including the development of data analysis and visualisation pipelines. 5
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) The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena
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datasets, performing statistical analyses and machine learning approaches to identify biomarkers of treatment responses. The candidate will also develop and implement bioinformatics pipelines in a high
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within a Research Infrastructure? No Offer Description Introduction As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the
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. This project involves the development and application of interpretable machine learning methods to uncover allosteric regulation of disordered regions in the dynamics of G-protein coupled receptors to enable
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for active learning. The role will work at the intersection machine learning, high-throughput computation, and inorganic crystalline materials discovery, focusing on accelerating the design and